Triple

T2898320
Position Surface form Disambiguated ID Type / Status
Subject Arnold Bennett E62594 entity
Predicate notableWork P4 FINISHED
Object The Card
The Card is a comic novel by English writer Arnold Bennett that follows the ambitious rise of the charming and enterprising Edward Henry Machin in the fictional Five Towns.
E307745 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: The Card | Statement: [Arnold Bennett, notableWork, The Card]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Card
Context triple: [Arnold Bennett, notableWork, The Card]
  • A. Troika card
    The Troika card is a reusable contactless smart card used for paying fares across Moscow’s public transportation system.
  • B. Go-To Card
    The Go-To Card is a reusable, contactless smart card used to pay fares on the Minneapolis–Saint Paul METRO transit system.
  • C. Cardiac Cards
    Cardiac Cards is a nickname for the former St. Louis Cardinals NFL team, referencing their dramatic, late-game comebacks and close finishes.
  • D. Nol card
    The Nol card is a rechargeable smart card used for paying fares across Dubai’s public transportation network, including metro, buses, trams, and water buses.
  • E. Card
    Card is a surname most notably borne by Andrew Card, a former White House Chief of Staff under U.S. President George W. Bush.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: The Card
Triple: [Arnold Bennett, notableWork, The Card]
Generated description
The Card is a comic novel by English writer Arnold Bennett that follows the ambitious rise of the charming and enterprising Edward Henry Machin in the fictional Five Towns.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: The Card
Target entity description: The Card is a comic novel by English writer Arnold Bennett that follows the ambitious rise of the charming and enterprising Edward Henry Machin in the fictional Five Towns.
  • A. Troika card
    The Troika card is a reusable contactless smart card used for paying fares across Moscow’s public transportation system.
  • B. Go-To Card
    The Go-To Card is a reusable, contactless smart card used to pay fares on the Minneapolis–Saint Paul METRO transit system.
  • C. Cardiac Cards
    Cardiac Cards is a nickname for the former St. Louis Cardinals NFL team, referencing their dramatic, late-game comebacks and close finishes.
  • D. Nol card
    The Nol card is a rechargeable smart card used for paying fares across Dubai’s public transportation network, including metro, buses, trams, and water buses.
  • E. Card
    Card is a surname most notably borne by Andrew Card, a former White House Chief of Staff under U.S. President George W. Bush.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe08fe3248190a6bb7de2a2c317b1 completed March 7, 2026, 8:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69b03188d84081909e23b46c2f75250b completed March 10, 2026, 2:58 p.m.
NEDg Description generation batch_69b036ef40188190880dfe3592107b0e completed March 10, 2026, 3:21 p.m.
NED2 Entity disambiguation (via description) batch_69b03bca591c81908b3734cc8f2e712b completed March 10, 2026, 3:42 p.m.
Created at: March 6, 2026, 10:10 p.m.